95 results about "Current analysis" patented technology

The invention discloses a sample self-relay method for laboratory real-time quality control and an automatic system, and belongs to the technical field of clinical laboratory automatic quality control. According to the method, an independent quality control cycle is established for a plurality of preset key concentrations, and a concentration-bias and concentration-inaccuracy mapping table is established based on historical quality control data. Independent counting is maintained for each target concentration, when the detection number reaches the length L of the current analysis batch, quality control is automatically triggered, two patient samples with the concentrations meeting the requirements are screened from the current detection batch to serve as a self-relay quality control sample pair, and judgment is conducted according to the rule of 1-3 s after returning and re-detection. And meanwhile, querying a mapping table according to the actual concentration of the sample to calculate a sigma value, querying a preset sigma-L mapping table based on the sigma value, and dynamically updating the next analysis batch length of the target concentration. Each cycle operates independently and asynchronously to form a closed loop, so that accurate, automatic and real-time quality control of different concentrations and different frequencies is realized, and the implementation bottleneck of personalized 6 sigma quality control in cost and reliability is overcome.

The invention discloses a low-voltage cabinet and an operation environment monitoring and early warning system thereof, and belongs to the technical field of low-voltage electrical equipment monitoring. The system comprises an information acquisition module, an electromagnetic environment analysis module, an in-cabinet environment analysis module, an operation activity analysis module, a temperature-leakage current analysis module and a flow rate optimization module. A plurality of environmental coefficient and collaboration models are constructed by collecting various indexes such as electromagnetism, gas, air pressure, operation frequency and the like, temperature and leakage current thresholds are dynamically calibrated, and the air velocity in the cabinet is optimized based on a temperature-leakage current collaboration coefficient and an operation activity coefficient. The system can comprehensively sense the operation state of the low-voltage cabinet, achieves precise early warning and intelligent ventilation, and effectively improves the operation safety and energy efficiency level of equipment.

The invention provides a picoampere-level current measuring device and method with leakage estimation and digital compensation, and the device comprises an electrometer-level operational amplifier and a transimpedance feedback network which are used for converting a measured current into a voltage signal; in combination with a retaining ring conductor driven by a retaining ring buffer and an inner and outer double-layer metal shielding structure, high-resistance node leakage and external interference are remarkably reduced. The digital controller injects 5mV-50mV micro excitation into the retaining ring in a non-sampling window and detects output response so as to estimate input equivalent leakage conductance and perform online compensation; and meanwhile, environment self-adaptive correction is carried out according to a temperature and humidity-leakage admittance model. The system adopts a 24-bit analog-to-digital converter, two-stage zero-drift amplification and multi-point linearity calibration can be switched, picoampere-level current measurement with high precision, low noise and wide dynamic range is realized, and the system is suitable for the fields of high-insulation detection, light current measurement, electrochemical micro-current analysis and the like.

The invention discloses a training method and device for an electroencephalogram data analysis model and electronic equipment. The method comprises the steps that electroencephalogram training data are collected; the electroencephalogram training data is electroencephalogram signals formed when the target object controls a cursor in a preset training graph to move according to a preset intention; analyzing the electroencephalogram training data based on the current analysis model to obtain a cursor brain control signal; the current analytical model is determined from a historical model library; determining a control result based on the current brain control proportion and the cursor brain control signal; training a preset model to obtain an electroencephalogram data analysis model, and storing the electroencephalogram data analysis model to a historical model library; meanwhile, the current brain control proportion is adjusted based on the control result, the process is repeated till training is finished, and the current analysis model after training is finished is determined as the target electroencephalogram data analysis model. According to the training method, the electroencephalogram data analysis model can be efficiently and conveniently trained, so that the model is periodically and rapidly updated, and the model in actual use can adapt to changes of physiological features of a user.

The invention discloses a DC fault current analysis and calculation method suitable for multi-type MMC converters, and the method comprises the steps: determining the topology type of an MMC converter related to a fault line, and collecting core parameters; constructing an RLC series unified equivalent circuit model of the MMC, and correcting the RLC series unified equivalent circuit model based on the topology type to obtain an equivalent circuit correction model; and determining a DC fault current based on the equivalent circuit correction model. According to the method, a technical architecture of'unified modeling + differential correction 'is constructed, multiple types of MMC converters are abstracted into an RLC basic equivalent model, local parameter correction is carried out only for fault characteristic differences of different topologies, and the tedious process of repeated modeling is effectively avoided; meanwhile, converter active current limiting strategies such as locking and negative input control are considered in the modeling process of fault current analytical calculation, the model architecture has good expansibility, various control strategies can be flexibly fused, and deep fusion of the electromagnetic transient process and the control process is achieved.

Embodiments of the present application provide a method, medium and electronic device for automatic data analysis, the method comprising: obtaining an original data file and a current analysis target; obtaining a target data table according to initial data characteristics of the original data file; obtaining updated data characteristics corresponding to the original data file according to the target data table; inputting the updated data characteristics and the current analysis target into a pre-constructed analysis method recommendation knowledge base to obtain a candidate analysis method set; performing effect simulation pre-evaluation on at least part of the analysis methods in the candidate analysis method set according to the target data table to obtain real-time performance evaluation indexes of each method; obtaining a target analysis method selected for the current analysis target based on a reinforcement learning decision model; and analyzing the target data table using the target analysis method to generate an analysis result.

The application provides a power system stability analysis method based on impedance measurement data, comprising determining that the current analysis condition is a condition corresponding to an equivalent circuit diagram based on a converter topology structure diagram, wherein a disturbance voltage source is in series or a disturbance current source is in parallel; under the current analysis condition, disturbance voltage components and disturbance current components generated on the converter side are obtained to obtain converter impedance measurement data carrying amplitudes and phase angles at several frequency points, and disturbance voltage components and disturbance current components generated on the power grid side are obtained to obtain power grid equivalent impedance measurement data carrying amplitudes and phase angles at several frequency points; the converter impedance measurement data and the power grid equivalent impedance measurement data at the same frequency point are compared, and according to each comparison result, the risk of oscillation instability of the power system is judged. The application is implemented to reduce the complexity of impedance measurement operation, thereby improving the analysis accuracy.

This application discloses a method and apparatus for constructing a parallel current source model for IGBT turn-off current analysis. The main scheme is as follows: Based on the physical nature of the IGBT turn-off current decrease process, it is revealed that it includes two synchronously occurring sub-processes (the carrier injection process and the carrier recombination reduction process corresponding to MOSFET turn-off); the IGBT turn-off current is defined as the parallel superposition of the currents (injection current and recombination current) generated by these two sub-processes; this abstract "dual current" physical theory is transformed into an equivalent circuit composed of a controlled source and a current source connected in parallel; the two sub-processes are analyzed in this way: for the first sub-process, a first relationship characterizing the dynamic evolution law of the injection current is derived; for the second sub-process, a second relationship characterizing the dynamic evolution law of the recombination current is derived; finally, by combining these two relationships, a parallel current source model for quantitatively characterizing the IGBT turn-off current decrease process is constructed.

This invention relates to the field of power management and anomaly detection technology, specifically to a method and system for detecting anomalies in multi-port charging power supplies based on current analysis. It is applied to a charging system containing multiple load power supply buses and several branch switching transistors. The method includes: extracting and sampling AC ripple current from the total current signal of the multiple load power supply buses and each branch; performing delay mapping on the AC ripple current to construct a multi-dimensional phase space matrix and calculate a Poincaré cross-section scatter plot; calculating the current topological information entropy based on the scatter distribution probability and comparing it with the baseline information entropy to generate an information entropy residual; comparing the information entropy residual with a safety manifold boundary threshold range, determining a charging anomaly when it exceeds the threshold, outputting a hardware interrupt signal to control the state of the corresponding branch switching transistor, and generating a diagnostic report containing physical feature parameters extracted based on the multi-dimensional phase space matrix. This invention enables early identification of anomalies in multi-port charging systems and rapid hardware-level response.

This invention relates to the technical field of circuit breaker analysis, specifically to an intelligent monitoring system for circuit breaker characteristics based on opening and closing identification. The system includes: a current analysis module for analyzing changes in current data of the circuit breaker at various monitoring times to obtain multiple opening and closing current characteristic indices; a temperature analysis module for analyzing changes in contact temperature data of the circuit breaker at various monitoring times to obtain multiple opening and closing temperature characteristic indices; an identification module for identifying at least one first index and at least one second index; a consistency analysis module for analyzing the consistency between the data sequences corresponding to the first index and the data sequences corresponding to the second index to obtain multiple time-related indices; and an opening / closing determination module for determining the monitoring time indicated by the current data corresponding to the largest time-related index as the opening / closing time of the circuit breaker. This invention enables accurate acquisition of the opening and closing time of the circuit breaker.

The invention belongs to the technical field of underground structure tests, and provides an underground structure hybrid test system considering stratum loss and a control method.The system comprises a numerical substructure used for determining boundary node displacement on an interaction boundary corresponding to a current analysis step; the virtual test substructure is used for calculating a boundary node force according to the boundary node displacement and the current gravity, obtaining a node force simulation value by combining a similarity coefficient, and further determining a concentrated force for loading; the test substructure is used for acquiring loading force and displacement data through concentrated force; and the parameter inversion module is used for performing inversion on the loading force and the displacement data to obtain material parameters under the current boundary condition so as to update the numerical model and the boundary node force of the test substructure and further determine the target unbalanced force, so that the interaction boundary between the structures meets displacement coordination and force balance. According to the system, refined simulation of a multi-field coupling mechanism under complex geological conditions is realized, and the stratum loss simulation accuracy is improved.

The invention discloses a sensorless field-oriented control motor driving method and device for a molecular pump, and relates to the technical field of molecular pumps, and the method comprises the steps: S1, starting a motor, and obtaining related data; s2, positioning a rotor; s3, rotor acceleration; s4, judging whether a stable condition is met or not, if so, entering S5, and otherwise, returning to S3; s5, obtaining related data; s6, whether the rotor speed reaches the standard or not is judged, if yes, S13 is executed, and if not, S7 is executed; s7, analyzing the current component and the current; s8, analyzing a back electromotive force component; s9, analyzing a rotor angle estimation value and an angular velocity estimation value; s10, outputting a voltage instruction; s11, generating and compensating a PWM driving signal; s12, driving the three-phase inverter, and returning to S5; s13, judging whether to stop or not, if so, stopping, and if not, stably operating; counter electromotive force estimation, rotor angle tracking, current control and starting and closed-loop switching processes are cooperatively designed, so that the problem of insufficient suitability of a traditional scheme in application of the molecular pump is solved, and the high-speed and high-torque requirements of the adaptive molecular pump are met.

The invention provides a network flow analysis method, device, equipment and medium, and the method comprises the steps: analyzing a packet header of any data packet, and when the packet header of any data packet is analyzed to a tunnel encapsulation layer protocol, if the tunnel encapsulation layer protocol is a multi-protocol label switching protocol, sending the packet header of any data packet to a network; the method comprises the following steps of: storing a first analysis result which comprises metadata extracted from header information of each layer of protocol which is analyzed at present when a label stack of a multi-protocol label switching protocol is analyzed and a protocol type identifier which cannot be analyzed exists in a current analysis position of the label stack of the multi-protocol label switching protocol is identified, and then returning to an initial analysis position of the label stack so as to obtain a second analysis result which comprises metadata extracted from header information of each layer of protocol which is analyzed at present; and determining a target analysis protocol from the protocol feature library, and performing analysis again from the initial analysis position to obtain a second analysis result, thereby determining a stream analysis result based on the first analysis result, the second analysis result and third analysis results of the remaining protocols. According to the embodiment of the invention, information loss in an analysis process can be avoided.

The invention relates to the technical field of power electronic devices, in particular to a lightning arrester testing device and method, and the device comprises a first chamber, a second chamber and a third chamber which are provided with a passive shielding layer and an active shielding layer. The first chamber is provided with a first acquisition unit; the second chamber is used for extracting a leakage current component and a pulse response signal component from the mixed signal output by the first acquisition unit, and calculating a resistive current according to the leakage current component; the main control unit is used for analyzing a pulse response signal component to obtain a discharge counting result, and the signal processing unit is used for receiving and transmitting an electromagnetic interference signal detected by the active shielding layer to the main control unit, responding to an elimination instruction of the main control unit and generating and outputting an anti-interference signal; and the third chamber is provided with a pulse output unit which is used for responding to a pulse output instruction of the main control unit and outputting a corresponding pulse signal to the lightning arrester, so that the technical problem that a leakage current test and a discharge counting test are difficult to carry out simultaneously by an existing lightning arrester test device is solved.

This invention discloses an automated operation and maintenance method, system, device, and medium for new electricity meters in a distribution network. The method includes: responding to a new meter association request uploaded by a metering terminal to verify if the new meter address exists in a preset metering archive; if not, creating a temporary file for the new meter and issuing a topology identification command to the metering terminal; receiving characteristic current analysis results and new meter data from the metering terminal; updating the temporary file based on the characteristic current analysis results, branches, phases, and new meter data, and synchronizing the updated temporary file to the marketing master station; receiving the operation and maintenance handheld device verification results forwarded by the marketing master station; if the verification passes, instructing the marketing master station to convert the temporary file into a formal marketing file, and instructing the metering terminal to write the formal marketing file into the new meter to achieve operation and maintenance. Therefore, this application can achieve efficient, accurate, and automated operation and maintenance management after the installation of new meters.

This invention relates to the field of transformer monitoring technology, specifically to an online monitoring device and handling system for grounding current of transformer core and clamps. The system includes a data acquisition module, a current analysis module, a linkage analysis module, an early warning determination module, and a fault determination module. First, it analyzes the current surge and relative stability of the current data to determine the linkage characteristic of the current surge; then, it removes background current to obtain the true fault current; it determines the synchronization of the linkage response time between current and temperature; combining the linkage characteristic of the current surge and the synchronization of the linkage response time, it determines the early warning value for a metallic grounding fault; when the early warning value for a metallic grounding fault exceeds the preset normal early warning range, it compares the characteristics of different fault locations at the current moment with those in the historical database to obtain the fault location corresponding to the current moment. This invention achieves intelligent fault location determination.

The present disclosure provides a method for providing a quotation, relating to the technical field of artificial intelligence. The method for providing a quotation comprises: obtaining a current transaction dialogue and extracting transaction basic information therefrom; respectively analyzing transaction demand analysis on the current transaction dialogue based on a large corpus and a small corpus, the small corpus comprising a corpus constructed for an initiator of the current transaction dialogue; calculating a group stability index of the small corpus according to a historical analysis result of the small corpus; determining at least one of the large corpus and the small corpus as a target corpus according to the group stability index; and generating a reference quotation matched with the current transaction dialogue according to the transaction basic information and a current analysis result of the target corpus. The present disclosure also provides a device for providing a quotation, equipment, a storage medium and a program product.

The utility model discloses a multifunctional earth screen monitoring device which at least has the following beneficial effects: a power supply module; the control module is connected with the power supply module; the intelligent analysis module is connected with the control module, and the intelligent analysis module is used for obtaining the peak value, the wave head time, the wave tail time and the gradient of the lightning stroke current; and the lightning stroke current detection module is connected with the intelligent analysis module, and the lightning stroke current detection module is arranged on the earth screen main line and is used for obtaining the transient waveform of the lightning stroke current. According to the technical scheme of the embodiment, the lightning stroke type and the corrosion degradation trend of the ground screen can be effectively judged.

The invention discloses an intelligent analysis method and system fusing a space-time knowledge graph and structured reasoning, and the method comprises the steps: firstly collecting multi-source event data, carrying out the element analysis, and extracting structured data comprising entities, events, attributes, spatial positions and time elements; then converting the analyzed structured data into a triple form, writing the triple form into a space-time knowledge graph, and dynamically retrieving a local sub-graph related to the current analysis object in the space-time knowledge graph by taking event semantics, a spatial position and a time element as constraint conditions; and introducing the screened local sub-graph as an external knowledge constraint into a reasoning process of an intelligent reasoning model based on chain reasoning to realize intelligent analysis under the spatial-temporal knowledge constraint. According to the method, multi-dimensional information analysis, traceable reasoning analysis and result generation of the multi-source event data are realized, so that the reliability and response efficiency of intelligent analysis and decision support in a complex scene are improved.

The embodiment of the invention provides a performance monitoring method and related equipment, and belongs to the technical field of big data. The method comprises the following steps: acquiring a system attention index, a current time range and a current node dimension; extracting and screening database data based on the system attention index, the current time range and the current node dimension to obtain current data; acquiring a water level rule corresponding to the system attention index; judging whether the current data has a bottleneck or not based on a system program water level rule and a machine resource water level rule through the large language model, and if the current data has the bottleneck, determining a bottleneck type and abnormal data through the large language model; and generating a current analysis report based on the bottleneck type and the abnormal data through a large language model. According to the embodiment of the invention, the performance problem in the big data link can be found and solved in time, an analysis result can be provided for the performance problem on the big data link, and a user can visually know the bottleneck condition.

This invention discloses a multimodal perception-based intelligent integration system and method for duty information, specifically relating to the field of public security duty information processing technology. It addresses the problem of mismatch between existing front-end data compression methods and the specific task requirements of back-end big data analysis platforms, leading to the loss of key feature information and affecting analysis reliability. By parsing task instructions to form a feature requirement set, and based on this, evaluating the task contribution and cross-modal collaborative gain of the original perception data, it intelligently generates a compression control strategy tailored to the current analysis task. Finally, it performs differentiated compression and reorganization of the original data, forming a task-optimized data stream that is fed back to the back-end platform. This improves the value density and analytical relevance of the returned data, effectively ensuring the efficiency and accuracy of the back-end big data analysis platform under resource-constrained conditions.

The invention relates to the technical field of railway electric traction transmission, in particular to an irregular wheel wear detection method based on stator current analysis, which comprises the following steps of: constructing an electromechanical coupling model of a high-speed train traction transmission system based on a traction variable-current driving model and a train-track coupling power model; secondly, based on an electromechanical coupling model, the influence of irregular wear of the wheel on electrical parameters in an electric driving system is analyzed, and the frequency relation between irregular wear excitation and the electrical parameters (stator harmonic current) is established; and by constructing a comb filter based on variable mode decomposition, accurate capture of wheel wear related harmonic waves in stator current is realized, so that irregular wear of the wheel is detected, additional installation of a sensor is not needed, the cost is low, the method is not liable to be interfered by the external environment, and the method has relatively good engineering applicability.

The invention relates to the technical field of power system relay protection, and discloses a DC fault current processing method and system for a DR-MMC hybrid cascade system. The method comprises the following steps: dividing a DC fault process of the DR-MMC hybrid cascade converter into a plurality of fault stages based on fault loop state change; the fault current dynamic change characteristic of each fault stage is analyzed, and a fault current analysis sub-result of the corresponding fault stage is determined; integrating each fault current analysis sub-result according to the time interval of the corresponding fault stage, and determining a fault current analysis result of the DR-MMC hybrid cascade converter covering the DC fault process; and parameter optimization is carried out on the DR-MMC hybrid cascade converter based on the fault current analysis result, and the safe operation boundary of the DR-MMC hybrid cascade system is determined. The method provides a theoretical basis for fault protection design, equipment selection and safe and stable operation of the DR-MMC hybrid cascade system.

The invention provides an AI algorithm lightweight loading and cross-layer resource dynamic scheduling method and system, and the method comprises the steps: carrying out the model preprocessing of an original AI model at a central cloud side, generating a lightweight model, and meeting the volume compression ratio and precision loss constraints; resource states of all levels in the end side device, the edge computing node and the central holder are collected in real time, and the resource states comprise computing power, memory, network bandwidth and task load information; acquiring a current analysis task, and based on the resource state and the task demand of the current analysis task, calling the resource scheduling optimization model to solve the distribution proportion of an optimal task by adopting a genetic algorithm so as to minimize the processing time delay; and issuing the lightweight model to edge side and end side equipment, and allocating the current analysis task to three layers of end side, edge and cloud for execution according to the allocation proportion. The method has the effects of lightweight algorithm loading, efficient resource scheduling, high dynamic adaptability, high platform universality and low deployment cost.

The invention relates to the technical field of advertisement abnormal traffic detection, in particular to an internet advertisement abnormal traffic detection method and system, and the method comprises the steps: collecting the visited frequency and user stay duration of a target advertisement in each preset time period in a plurality of historical collection cycles; constructing target advertisement browsing time anomaly, a target advertisement browsing anomaly factor and a visited frequency change anomaly value, and fusing to generate a first anomaly value of target advertisement traffic; and constructing a user behavior abnormal value, combining the first abnormal value with the user behavior abnormal value, constructing a second abnormal value of the target advertisement flow, and constructing a flow judgment threshold value according to the second abnormal value of the time period in all historical collection periods so as to judge whether the advertisement flow is abnormal in the current analysis time period. According to the invention, the abnormal condition of the advertisement flow is accurately discriminated in combination with multi-aspect monitoring parameters.

The invention discloses a four-dimensional data assimilation method and system fused with space-time observation, and relates to the technical field of numerical weather forecast, and the method comprises the steps: generating a small set containing a plurality of set members based on a current analysis field, and enabling the set members to be generated through applying initial disturbance; performing short-time integration on the small set, covering and assimilating a time window, and outputting state variable sequences of set members at different time layers; and calculating a background error covariance evolved along with time by using the state variable sequence. According to the four-dimensional data assimilation method provided by the invention, the background error covariance evolved along with time and the static background error covariance are dynamically fused, the change characteristics of the atmospheric system on different time and spatial scales are effectively captured, especially in weather violent change areas such as strong oblique pressure and active convection, the error description precision is remarkably improved, and the method has the advantages of being high in robustness and high in robustness. The fusion mode of multiple types of observation data is optimized, and the propagation efficiency of observation information in a time window is enhanced.

Computing systems, methods, and non-transitory computer-readable storage media are provided. Identifier collisions are determined in historical event data based on short identifiers associated with geographically dispersed first and second event locations. Behavior analytics are performed on multiple short identifiers in the historical event data to generate behavioral models associated with the multiple short identifiers. Adjusted behavioral models are generated based on the determined identifier collisions. A short identifier is obtained and an adjusted behavioral model is determined. A new event value for a first event type is calculated when a total value of events of the first event type during a current analysis period does not exceed a baseline value associated with the first event type. A client device is notified using the new event value, whereby the client device displays a notification regarding the new event value in response to receiving the new event value.

The invention discloses a data analysis method, device and equipment, and relates to the technical field of data processing.The method comprises the steps that an initial target index is selected, and an initial analysis view is generated; in response to a received drill-down request of a newly-added index or a newly-added dimension initiated by a user in the initial analysis view, obtaining the index and the dimension selected in the initial analysis view as a current analysis context; based on the current analysis context, performing consistency verification on the drill-down request, and generating a compliance index or compliance dimension; based on a preset recommendation strategy, processing the compliance index or the compliance dimension to generate a recommended drill-down option; and updating the analysis view according to a selection instruction of the user in the recommended drill-down options to form a new current analysis view. Through dynamic logic verification and multi-layer intelligent guidance, the dependence on personal experience is reduced, standardized, automatic and intelligent attribution analysis is converted, and the complex attribution analysis efficiency is improved.

The embodiment of the invention provides a fractional order model historical data storage calling method and system, and relates to the technical field of finite element analysis. According to the method, after a binary direct access external file system is constructed, a historical variable index tag can be established based on unit numbers, Gaussian integral points and time dimension information associated with a fractional order model. And when the current analysis data is obtained, calculating a write-in address of the current analysis data in the external file system according to the historical variable index tag, and writing the current analysis data into the external file system. And when the historical cycle is started, reversely calculating a reading address corresponding to each past time dimension according to the historical variable index tag, and capturing historical data from the external file system to the temporary variable. According to the method, the double-precision floating-point number strictly occupies 8 bytes through binary storage, the utilization rate of the storage space is improved, and the calculation efficiency is improved by establishing a storage and reading path of an external file system.

This invention relates to a method for determining system state variables (x) in a fuel cell system (1) at successive analysis moments. (i+1) A computer-implemented method for the fuel cell system (1) wherein the following steps are performed at each current analysis time (i+1): - Determine (S2) one or more operating state variables (y) of the fuel cell system (1) at the current analysis time (i+1). (i+1) ); - Using a trained recurrent neural network, based on the internal state vector (h) of the recurrent neural network at the previous analysis time (i) (i) And based on the running state variable (y) determined at the current analysis time (i+1) (i+1) To determine (S3) the current system state variable (x) (i+1) The internal state vector describes the internal state of the fuel cell system (1); and - based on the currently determined system state variable (x) (i+1) (S3) to run the fuel cell system (1).